Text-to-Image
Diffusers
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use anic87/poor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use anic87/poor with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("anic87/poor", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks poorly-differentiated-adenocarcinoma" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 9a1c0dab3ec2f84a735790222b650321f9b7b33b930cb8861bb7dbb12b20699c
- Size of remote file:
- 3.44 GB
- SHA256:
- 83a374b8289de180cff33d9103a97fd840433b5dca5172d9e76cbf6e235927a5
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